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Machine learning in nephrology: scratching the surface

Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machi...

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Autores principales: Li, Qi, Fan, Qiu-Ling, Han, Qiu-Xia, Geng, Wen-Jia, Zhao, Huan-Huan, Ding, Xiao-Nan, Yan, Jing-Yao, Zhu, Han-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190222/
https://www.ncbi.nlm.nih.gov/pubmed/32049747
http://dx.doi.org/10.1097/CM9.0000000000000694
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author Li, Qi
Fan, Qiu-Ling
Han, Qiu-Xia
Geng, Wen-Jia
Zhao, Huan-Huan
Ding, Xiao-Nan
Yan, Jing-Yao
Zhu, Han-Yu
author_facet Li, Qi
Fan, Qiu-Ling
Han, Qiu-Xia
Geng, Wen-Jia
Zhao, Huan-Huan
Ding, Xiao-Nan
Yan, Jing-Yao
Zhu, Han-Yu
author_sort Li, Qi
collection PubMed
description Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machine learning models have yielded many preliminaries to moderate and several excellent achievements in the fields, including analysis of renal pathological images, diagnosis and prognosis of chronic kidney diseases and acute kidney injury, as well as management of dialysis treatments. However, it is just scratching the surface of the field; at the same time, machine learning and its applications in renal diseases are facing a number of challenges. In this review, we discuss the application status, challenges and future prospects of machine learning in nephrology to help people further understand and improve the capacity for prediction, detection, and care quality in kidney diseases.
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spelling pubmed-71902222020-08-05 Machine learning in nephrology: scratching the surface Li, Qi Fan, Qiu-Ling Han, Qiu-Xia Geng, Wen-Jia Zhao, Huan-Huan Ding, Xiao-Nan Yan, Jing-Yao Zhu, Han-Yu Chin Med J (Engl) Review Articles Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machine learning models have yielded many preliminaries to moderate and several excellent achievements in the fields, including analysis of renal pathological images, diagnosis and prognosis of chronic kidney diseases and acute kidney injury, as well as management of dialysis treatments. However, it is just scratching the surface of the field; at the same time, machine learning and its applications in renal diseases are facing a number of challenges. In this review, we discuss the application status, challenges and future prospects of machine learning in nephrology to help people further understand and improve the capacity for prediction, detection, and care quality in kidney diseases. Wolters Kluwer Health 2020-03-20 2020-03-20 /pmc/articles/PMC7190222/ /pubmed/32049747 http://dx.doi.org/10.1097/CM9.0000000000000694 Text en Copyright © 2020 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Review Articles
Li, Qi
Fan, Qiu-Ling
Han, Qiu-Xia
Geng, Wen-Jia
Zhao, Huan-Huan
Ding, Xiao-Nan
Yan, Jing-Yao
Zhu, Han-Yu
Machine learning in nephrology: scratching the surface
title Machine learning in nephrology: scratching the surface
title_full Machine learning in nephrology: scratching the surface
title_fullStr Machine learning in nephrology: scratching the surface
title_full_unstemmed Machine learning in nephrology: scratching the surface
title_short Machine learning in nephrology: scratching the surface
title_sort machine learning in nephrology: scratching the surface
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190222/
https://www.ncbi.nlm.nih.gov/pubmed/32049747
http://dx.doi.org/10.1097/CM9.0000000000000694
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